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    Inter-system and event-triggered mobility load balancing
    93.
    发明授权
    Inter-system and event-triggered mobility load balancing 有权

    公开(公告)号：US11968563B2

    公开(公告)日：2024-04-23

    申请号：US17371998

    申请日：2021-07-09

    Applicant: QUALCOMM Incorporated

    Inventor： Shankar Krishnan ,  Xipeng Zhu ,  Rajeev Kumar ,  Gavin Bernard Horn

    IPC: H04W28/086 ,  H04W24/10 ,  H04W28/02 ,  H04W28/08

    CPC classification number: H04W28/0865 ,  H04W24/10 ,  H04W28/0284 ,  H04W28/0958

    Abstract: Methods, systems, and devices for wireless communications are described. Some wireless communications system may utilize an inter-system information report message (e.g., a self-organizing network (SON) information report message) to support inter-system mobility load balancing (MLB). For example, a first node, operating in accordance with a first radio access technology (RAT), may receive an information report message from a second node operating in accordance with a second RAT. The information report message may include a periodic load reporting request information element (IE) or an event-triggered load reporting request IE. In response, the first node may determine a traffic load based on the load reporting request and transmit, to the second node, an information report message which includes one or more IEs for reporting the determined traffic load. The exchange of the load information via the IEs may enable for MLB between nodes of different RAT.

    Selective measurement reporting for a user equipment
    95.
    发明授权
    Selective measurement reporting for a user equipment 有权

    公开(公告)号：US11937114B2

    公开(公告)日：2024-03-19

    申请号：US17444437

    申请日：2021-08-04

    Applicant: QUALCOMM Incorporated

    Inventor： Rajeev Kumar ,  Xipeng Zhu ,  Shankar Krishnan ,  Ozcan Ozturk ,  Masato Kitazoe ,  Gavin Bernard Horn

    IPC: H04W24/10 ,  H04W24/08 ,  H04W76/10

    CPC classification number: H04W24/10 ,  H04W24/08 ,  H04W76/10

    Abstract: A method of wireless communication includes determining, based on a plurality of network measurements performed by a user equipment (UE), one or more measurement log files associated with the plurality of network measurements. The method further includes receiving, by the UE from a network device, a request associated with the one or more measurement log files. The request indicates at least one measurement filter. The method further includes transmitting, by the UE to the network device, a response to the request. The response includes first measurement results of the one or more measurement log files selected based on the at least one measurement filter and excludes second measurement results of the one or more measurement log files based on the at least one measurement filter.

    SYSTEMS AND METHODS OF PARAMETER SET CONFIGURATION AND DOWNLOAD
    96.
    发明公开
    SYSTEMS AND METHODS OF PARAMETER SET CONFIGURATION AND DOWNLOAD 审中-公开

    公开(公告)号：US20240064065A1

    公开(公告)日：2024-02-22

    申请号：US17891974

    申请日：2022-08-19

    Applicant: QUALCOMM Incorporated

    Inventor： Rajeev KUMAR ,  Xipeng Zhu ,  Gavin Bernard Horn ,  Aziz Gholmieh

    IPC: H04L41/16 ,  H04W76/11

    CPC classification number: H04L41/16 ,  H04W76/11

    Abstract: Example implementations include a method, apparatus and computer-readable medium of wireless communication by a user equipment (UE), comprising receiving parameter set configuration information from a network entity, the parameter set configuration information corresponding to a model structure employed in a machine learning operation by the UE for the wireless communication. The implementations further include activating a parameter set in response to an activation condition, the parameter set identified within the parameter set configuration information as being associated with the activation condition.

    CONDITIONAL ARTIFICIAL INTELLIGENCE, MACHINE LEARNING MODEL, AND PARAMETER SET CONFIGURATIONS
    97.
    发明公开
    CONDITIONAL ARTIFICIAL INTELLIGENCE, MACHINE LEARNING MODEL, AND PARAMETER SET CONFIGURATIONS 审中-公开

    公开(公告)号：US20230412470A1

    公开(公告)日：2023-12-21

    申请号：US17841339

    申请日：2022-06-15

    Applicant: QUALCOMM Incorporated

    Inventor： Rajeev Kumar ,  Xipeng Zhu ,  Shankar Krishnan

    IPC: H04L41/16 ,  G06N20/20

    CPC classification number: H04L41/16 ,  G06N20/20 ,  H04W88/02

    Abstract: Methods, systems, and devices for wireless communications are described. A user equipment (UE) may receive a message from a network entity indicating a set of machine learning models, a set of parameter sets, or both and one or more usage conditions associated with the machine learning models and parameter sets. Based on a usage condition being satisfied, the UE may select a machine learning model, a parameter set, or both for generating a machine learning inference. For example, the UE may select the machine learning model or the parameter set based on a priority, whether sufficient input data is provided, or based on other usage conditions. The UE may generate the machine learning inference using the selected machine learning model or the selected parameter set, and the UE may transmit a report indicating an output of the machine learning inference to the network entity.

    ML model training procedure
    100.
    发明授权
    ML model training procedure 有权

    公开(公告)号：US11818806B2

    公开(公告)日：2023-11-14

    申请号：US17323242

    申请日：2021-05-18

    Applicant: QUALCOMM Incorporated

    Inventor： Rajeev Kumar ,  Eren Balevi ,  Taesang Yoo ,  Xipeng Zhu ,  Gavin Bernard Horn ,  Shankar Krishnan ,  Aziz Gholmieh

    IPC: H04W16/22 ,  H04W88/08 ,  G06N20/00 ,  G06F18/214

    CPC classification number: H04W88/08 ,  G06F18/214 ,  G06N20/00

    Abstract: This disclosure provides systems, devices, apparatus, and methods, including computer programs encoded on storage media, for an ML model training procedure. A network entity may receive a trigger to activate an ML model training procedure based on at least one of an indication from an ML model repository or a protocol of the network entity. The network entity may transmit an ML model training request to activate the ML model training at one or more nodes. The one or more nodes may be associated with a RAN that may transmit, based on receiving the ML model training request, ML model training results indicative of a trained ML model. In aspects, an apparatus, such as a UE, may train the ML model based on an ML model training configuration received from the RAN, and transmit an ML model training report indicative of the trained ML model.

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